Mesoscale Meteorological Modeling

This second edition provides an update of the field of mesoscale atmospheric modeling. The topic of mesoscale modeling is developed from basic concepts in atmospheric physics. New numerical and analytical tools are introduced. Problem sets are provided to test the comprehension of the material introduced in the text.

The 3rd edition of Mesoscale Meteorological Modeling is a fully revised resource for researchers and practitioners in the growing field of meteorological modeling at the mesoscale. Pielke has enhanced the new edition by quantifying model capability (uncertainty) by a detailed evaluation of the assumptions of parameterization and error propagation. Mesoscale models are applied in a wide variety of studies, including weather prediction, regional and local climate assessments, and air pollution investigations. Broad expansion of the concepts of parameterization and parameterization methodology Addition of new modeling approaches, including modeling summaries and summaries of data sets All-new section on dynamic downscaling

This chapter provides a framework to assess the quantitative accuracy of numerical computational tools that are used to model advection, subgrid-scale fluxes, the pressure gradient force, and the Coriolis effect. Exact solutions are presented for linear forms of these terms. Nonlinear effects are also discussed including the concept of aliasing in which information is transferred between spatial scales. Among the results, it is shown that two grid increments are required to minimally resolve a modeled field with at least four increments in each spatial direction (and probably more) required to adequately resolve the modeled variables.

‘Mesoscale Modelling for Meteorological and Air Pollution Applications’ combines the fundamental and practical aspects of mesoscale air pollution and meteorological modelling. Providing an overview of the fundamental concepts of air pollution and meteorological modelling, including parameterization of key atmospheric processes, the book also considers equally important aspects such as model integration, evaluation concepts, performance evaluation, policy relevance and user training.

This chapter reports on the spatial scale of mesoscale systems, and then presents examples of mesoscale atmospheric systems. They are classed into two types, terrain- and physiographically-induced mesoscale systems, and mesoscale systems primarily forced through lateral boundaries or from internal atmospheric instabilities. Mesoscale model studies of Mars, Titan, and Venus are also introduced. The different types of dynamic downscaling to the regional and mesoscale from global models and reanalyses are presented. The use of mesoscale models to assess air quality is discussed.

The foundation for any model is a set of conservation principles. For mesoscale atmospheric models, these principles are conservation of mass, conservation of heat, conservation of motion, conservation of water, the conservation of other gaseous and aerosol materials, and an equation of state.

This book provides an overview of several components of mesoscale modeling: boundary conditions, subgrid-scale parameterization, moisture processes, and radiation. Also included are mesoscale model comparisons using data from the U.S. Army's Project WIND (Winds in Non-uniform Domains).

This chapter introduces the grid-volume average which is a space-time integration over the grid increments used in modeling. Among the terms resulting are subgrid-scale correlation terms.